juspy
juspy is a library for making EDA and Modelling in Python quick and convinient. It's built on top of:
- pandas
- numpy
- seaborn
- and many such great libraries
Our reccomended path of getting started with juspy
- Download & install Anaconda
- Open
Anaconda Prompt - In
Anaconda Prompttype
conda install -c conda-forge jupyterlab
- and then
pip install juspy
jupyterlab
Incase if you're having any trouble regarding installation or dependencies, kindly make sure you're using updated versions
conda update conda
conda update pip
conda update python
And now try the above steps again
Demo Notebooks:
-
To test library's proper installation and working:
import juspy print(juspy.__version__) from juspy import greet print(greet.namastey())
-
jpplot.confusion_matrix()
import numpy as np import seaborn as sns from sklearn.metrics import confusion_matrix y_true = [0, 1, 0, 1, 0, 1, 0] y_pred = [1, 1, 1, 0, 1, 0, 1] cf_matrix = confusion_matrix(y_true, y_pred) from juspy import plot as jpplot jpplot.confusion_matrix(cf_matrix)
-
jpplot.piechart()
import pandas as pd df_name = pd.read_csv("https://raw.githubusercontent.com/juspreet51/juspy/main/src/juspy/datasets/default.csv") from juspy import plot as jpplot jpplot.piechart(df_name["student"])
-
from juspy.linear_models import LinearRegression
from juspy.linear_models import LinearRegression as lin_reg
Future Release:
Metadata
Release files for juspy 0.0.1
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | |
|---|---|---|---|
| juspy-0.0.1.tar.gz | 4.3 kB | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| juspy-0.0.1-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 8.8 kB
Release files / juspy-0.0.1.tar.gz
| Download URL | juspy-0.0.1.tar.gz |
|---|---|
| Size | 4.3 kB |
| Tags | Source |
|
SHA-256 checksum How to use checksums |
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Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/3.6.0 importlib_metadata/4.8.1 pkginfo/1.7.1 requests/2.26.0 requests-toolbelt/0.9.1 tqdm/4.62.3 CPython/3.9.7
|
Release files / juspy-0.0.1-py3-none-any.whl
| Download URL | juspy-0.0.1-py3-none-any.whl |
|---|---|
| Size | 4.5 kB |
| Tags | Python 3 |
|
SHA-256 checksum How to use checksums |
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BLAKE2b-256 checksum How to use checksums |
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| Upload date | |
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Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/3.6.0 importlib_metadata/4.8.1 pkginfo/1.7.1 requests/2.26.0 requests-toolbelt/0.9.1 tqdm/4.62.3 CPython/3.9.7
|